Intruder Alert System

Soniya Komal V1, Sayyida Kaunain2, Sheefa Naaz3, Indrakumar M4 , Irfan Mohammed5

1Assistant Professor, Department of CSE, Rajiv Gandhi Institute of Technology, Visvesvaraya Technological University, Bangalore, India

2, 3, 4, 5UG Students, Department of CSE, Rajiv Gandhi Institute of Technology, Visvesvaraya Technological University, Bangalore, India

Abstract: In this paper, we present an intruder alert system that detects and classifies potential intruders in a given environment using computer vision and machine learning. A network of cameras and a central processing unit run an object detection algorithm and a machine learning classifier in the system. This project was designed and built with an Arduino mega microcontroller, system connected to a GSM module with SIM (subscriber identification module) from a network provider (LDR) sensor which is used in this project is connected to a microcontroller unit, GSM module, and other electronic devices which thus detect any intruder in a classified area, activates the alarm system, and sends text message notifications to the house owner specifying the location and time of intrusion to the house owner's programmed phone number. The design worked in real-time in an area with good network coverage, as expected, according to preliminary testing. It has a wide range of applications in surveillance, particularly in industrial and home security, where internet connectivity is unavailable. The findings demonstrate that the system is capable of accurately identifying and categorizing possible intruders with low rates of false positives.

Keywords: Machine learning, Object detection Algorithm, Microcontroller, GSM module, Surveillance

I. INTRODUCTION

Intruder alarm systems are an important tool for ensuring the safety and security of people and property. The concept of an integrated home security system is an important implementation to aid in the security of our family and home. When we examine various home automation systems over time, we can see that they have always attempted to provide home residents with dependable and secure methods of accessing their homes. On the other side, IoT is emerging today with a slew of apps in different sectors, including the security and surveillance industry. IoT technology may enhance home security by providing real-time monitoring, remote control, and security system automation. With the increasing availability of low-cost IoT devices, smart home security systems have become increasingly common and affordable to homeowners. Our system uses IoT devices like sensors, cameras, and smart locks to provide enhanced security features that traditional home security systems lack. This research aims to design and implement a low-cost intruder detector system with a connected mobile application using a similar approach but different control units and sensors.

Here are some of the objectives of the project:

1) Its goal is to detect if any unwanted strangers are following authorised personnel, effectively preventing intruders from circumventing the entrance security system.

2) To address the issue of inadequate home security by providing a direct method of improving it.

3) To use object detection to identify anyone standing outside the door.

4) To then notify the owner whether or not the person ringing the bell has authorised access.

5) Using a camera, provide visuals of who is at the door.

6) To send all of the aforementioned information to the user via a mobile application.

7) To give the user the ability to open the door if he or she recognises the person.

II. LITERATURESURVEY

An intruder alert system is a device that detects unauthorised entry into a secure area and alerts the appropriate personnel. A literature review on intruder alert systems reveals that several studies have been conducted on the design, development, and implementation of these systems. The following is a synopsis of some of the research papers published in this field:

1) The design and implementation of a wireless intruder alert system using ZigBee technology were presented in 2017. A control unit, sensors, and a wireless communication network make up the system. The findings demonstrate the system's capacity to identify intrusions and notify the necessary personnel.